Objective Heilongjiang Province is a major forestry province in China, which plays an important role in strategy of carbon peaking and carbon neutrality. The estimation of carbon storage and carbon sequestration capacity of major arbor forest types in Heilongjiang Province can provide theoretical support for future forest management of Heilongjiang Province.
Method Carbon density was calculated based on the fixed sample plot data of major arbor forest types in Heilongjiang Province, and age-carbon density growth curves of various arbor forests were constructed by the spatial-temporal method. Based on the forest area data of Heilongjiang Province, the carbon density and carbon storage of each age group of various arbor forest in Heilongjiang Province were estimated in base year and target year. The sample plots were classified according to the 10-year interval, and the current carbon sequestration potential of each class was obtained by calculating the difference between the highest value and the average value of carbon density of each class. The average total current carbon sequestration potential of each arbor forest type was calculated by weighting of the number of sample plots, and the calculation results were analyzed.
Result (1) The total carbon storage of arbor forest in Heilongjiang Province was 878.73 Tg, in which the proportion of carbon storage of middle-aged forest and near-mature forest was the largest, accounting for 37.85% and 24.21%, respectively. The total average carbon density was 52.599 t/ha, and total current carbon sequestration potential was 27.719 t/ha. (2) Among the major arbor forest types, broadleaved mixed nature forest accounted for the largest proportion of total carbon storage in 2015, followed by Quercus mongolica natural forest, accounting for 44.65% and 17.02%, respectively. In 2060, the two types with the largest carbon storage did not change, but the proportion of carbon storage declined. In 2015, the two arbor forests with the highest total average carbon density was Quercus mongolica natural forest and broadleaved mixed natural forest, with carbon density of 82.545 t/ha and 60.699 t/ha. The two forests with the highest total average carbon density in 2060 were Quercus mongolica natural forest and Populus davidiana natural forest, with carbon density of 103.659 t/ha and 92.255 t/ha, respectively. (3) Among all kinds of arbor forests, Populus davidiana natural forest, coniferous mixed plantation, and Pinus sylvestris var. mongholica plantation had higher carbon density growth, and the carbon density growth value of 2060 compared with the initial year was 36.805, 40.505 and 40.809 t/ha, respectively. (4) The total current carbon sequestration potential of all kinds of arbor forest was the highest in broadleaved mixed natural forest (31.536 t/ha), and the highest was mixed coniferous and broadleaved plantation (27.674 t/ha). In all age groups, the total current carbon sequestration potential of middle-aged forest was the highest of 29.179 t/ha.
Conclusion This study estimates the carbon density, carbon storage and current carbon sequestration potential of various age groups of major types of arboral forest in Heilongjiang Province from 2015 to 2060. For those arbor forests with high carbon storage and real carbon sequestration potential, but low carbon density growth in the future, such as broadleaved mixed natural forest and mixed coniferous and broadleaved plantation, it is necessary to strengthen the forest tending to promote the carbon density growth. The future new afforestation planning should be based on the conditions of suitable land and trees, and select more plantation types with higher carbon density growth in the future, such as Pinus sylvestris var. mongholica plantation and coniferous mixed plantation, etc. The renewal of natural forests should also focus on natural forest types with higher carbon density growth in the future, such as Populus davidiana natural forest. The conclusion can provide theoretical guidance for forest carbon sink management in Heilongjiang Province in the future.
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